We are facing a rapidly growing capability to collect more and more data regarding our environment. With that, we must have the ability to extract more insightful knowledge about the environmental processes at work on the earth. Spatio-temporal information systems (STIS) should prove beneficial in producing useful knowledge about changes in our world from these ever-burgeoning collections of environment data. STIS provide the ability to store, analyze and represent the dynamic properties of the environment, that is, geographic information in space and time. A STIS, for example, can produce a weather map, but more importantly, it can present a user with information in map or report form indicating how precipitation progresses in space over time to affect a watershed. Other uses include forestry and even electrical systems management. Forestry experts using an STIS are able to examine the rates of movements of forest fires, how they evolve over time, and their impact on forest growth over long periods of time. A large electrical network system manager uses an STIS to track the failures and repairs of electrical transformers.Use of an STIS in this case allows the reconstruction of the status of the network at any given past time. This title is an edited volume is composed of chapters from experts in the field and addresses the many issues in support of modelling, creation, querying, visualizing and mining. The book is intended to bring together a coherent body of knowledge relating to STIS data modelling, design, implementation and STIS in knowledge discovery. In particular, the reader is exposed to the most up-to-date techniques for the practical design of STIS, essential for complex query processing. It is structured to meet the needs of practitioners and researchers in industry and graduate-level students in computer science.
1: Spatio-Temporal Data Mining and Knowledge Discovery: Issues Overview.- 1. Introduction.- 2. Background.- 3. Data.- 4. Data Issues.- 5. Conclusions.- 2: Indexing of Objects on the Move.- 1. Introduction.- 2. Problem Statement and Related Work.- 3. The TPR-Tree.- 4. The REXP-Tree.- 5. Summary of Performance Experiments.- 6. Conclusions.- 3: Efficient Storage of Large Volume Spatial and Temporal Point-Data in an Object-Oriented Database.- 1. Introduction.- 2. The GIDB System.- 3. The Problem Domain.- 4. An Object-Oriented Solution.- 5. Requirements.- 6. Towards a Solution.- 7. The Design.- 8. A Flexible Framework.- 9. Sample Applications.- 10. Evaluation.- 11. Future Developments.- 12. Conclusions.- 4: A Typology of Spatiotemporal Information Queries.- 1. Introduction.- 2. Spatiotemporal Information for the Dynamic World.- 3. A Typology of Spatiotemporal Queries.- 4. Conclusions.- 5: Visual Query of Time-Dependent 3D Weather in a Global Geospatial Environment.- 1. Introduction.- 2. 4D Data Model for the Visual Earth.- 3. Scalable, Hierarchical 3D Data Structure.- 4. Interactive, Accurate Visualization of Nonuniform Data.- 6: STQL — A Spatio-Temporal Query Language.- 1. Introduction.- 2. Related Work.- 3. The Data Model.- 4. Querying with Spatio-Temporal Operations.- 5. Visual Querying.- 6. Conclusions.- 7: Tripod: A Spatio-Historical Object Database System.- 1. Introduction.- 2. Case Study: UK National Land Use Database.- 3. The Tripod Object Model.- 4. Architecture.- 5. Related Work.- 6. Conclusions.- 8: Spatio-Temporal Subgroup Discovery.- 1. Introduction: Spatial Subgroup Mining.- 2. Application Example.- 3. Representation of Spatio-Temporal Data and of Spatial Subgroups.- 4. Spatio-Temporal Analyses.- 5. Database Integration.- 6. Conclusions and Future Work.